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import java.util.ArrayList;
import java.util.List;
import java.util.Scanner;

enum State {
    NORMAL,SPACE,SINGLE,DOUBLE,ESCAPE
}

class Extractor {
    private State state; // 当前状态

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import QtQuick 2.12
import QtQuick.Window 2.12

Window {
    id: msPaint
    visible: true
    width: 640
    height: 480
    title: qsTr("MoeSoftPaint")

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from os import makedirs
from os.path import dirname, abspath
from pathlib import Path

from onnxruntime.quantization import quantize_dynamic, QuantType
from sentence_transformers import SentenceTransformer, util
import torch
from torch import nn

from transformers.onnx.convert import export_pytorch

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# Use https://github.com/harishanand95/diffusers to export

from pathlib import Path

import torch
import torch.nn as nn
from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler, DiffusionPipeline
from transformers import CLIPTextModel

class VQEncoder(nn.Module):

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import os
from PIL import Image

# 定义源目录和目标目录
source_dir = r"D:\dataset\before"
target_dir = r"D:\dataset\after"

# 遍历源目录下的所有图片文件
for filename in os.listdir(source_dir):
    # 打开图片文件

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#include "player.h"

using namespace std;

void data_callback(ma_device* pDevice, void* pOutput, const void* pInput, ma_uint32 frameCount) {
	AVAudioFifo* fifo = reinterpret_cast<AVAudioFifo*>(pDevice->pUserData);
	av_audio_fifo_read(fifo, &pOutput, frameCount);

	(void) pInput;
}

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[package]
name = "player"
version = "0.1.0"
edition = "2021"

# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html

[dependencies]
cpal = "0.13.5"
ffmpeg-next = "5.0.3"

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import json
import torch
import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from transformers.generation.utils import GenerationConfig


st.set_page_config(page_title="Baichuan-13B-Chat")
st.title("Baichuan-13B-Chat")

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import gradio as gr
import mdtex2html
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from transformers.generation.utils import GenerationConfig

# 模型路径
MODEL_PATH = 'Qwen/Qwen-7B-Chat'

CONTEXT_SIZE = 8192